Automated mobile device interface prediction and detection

Abstract

A method and system for improving an automated mobile device prediction and detection system is provided. The method includes automatically determining a user interaction portion of a mobile device. Predictive content keyboard functionality with respect to a GUI of the mobile is determined and device is enabled and associated sensor data is analyzed. A specified body part of the user being utilized for supporting the mobile hardware device is determined and a portion of the user interaction portion for presenting predictive content is additionally determined. In response, the GUI is modified. Input text data is received from the user and associated predictive terms are presented via the modified GUI such that the predictive terms are accessible via a portion of the specified body part of the user. A selection for a first predictive term of the predictive terms is received via the modified GUI.

What is claimed is: 
     
         1 . An automated mobile device prediction and detection improvement method comprising:
 automatically determining, by a processor of a mobile hardware device of a user, a user interaction portion of said mobile device, wherein said user interaction portion of said mobile hardware device is associated with executing predictive content selection actions;   enabling, by said processor in response to a command from said user, predictive content keyboard functionality with respect to a graphical user interface (GUI) of said mobile hardware device;   analyzing, by said processor, sensor data retrieved from sensors of said mobile hardware device;   determining, by said processor based on results of said analyzing, a specified body part of said user currently being utilized for supporting and retaining said mobile hardware device;   determining, by said processor based on results of said determining, a specified portion of said user interaction portion for presenting predictive content associated with input data retrieved via a keyboard of said GUI;   modifying, by said processor based on said results of said determining, said GUI such that said specified portion of said user interaction portion is presented at a specified location of said GUI associated with said specified body part of said user;   receiving, by said processor from said user, input text data;   presenting, by said processor within said specified portion of said user interaction portion at specified location of said GUI, predictive terms associated with said input text data such that said predictive terms are accessible via a portion of said specified body part of said user; and   retrieving, by said processor via said portion of said specified body part of said user, a selection of a first predictive term of said predictive terms.   
     
     
         2 . The method of  claim 1 , wherein said automatically determining said user interaction portion of said mobile device comprises:
 retrieving, by said processor from a remote database, a user profile describing user reachable portions of said user interaction portion.   
     
     
         3 . The method of  claim 1 , wherein said automatically determining said user interaction portion of said mobile device comprises:
 detecting, by said processor via said sensors, said portion of said specified body part of said user currently able to access said user interaction portion.   
     
     
         3 . The method of  claim 1 , wherein said user interaction portion of said mobile is reachable via a thumb of said user. 
     
     
         4 . The method of  claim 1 , wherein said sensors comprise an accelerometer and a gyroscope and wherein said analyzing comprises:
 detecting, by said processor via said accelerometer, vibrations initiated via said specified body part of said user; and   detecting, by said processor via said gyroscope, an angle of said specified body part of said user with respect to said mobile hardware device.   
     
     
         5 . The method of  claim 1 , wherein said sensors comprise a temperature sensor, and wherein said analyzing comprises:
 detecting, by said processor via said temperature sensor, a temperature of said mobile hardware device with respect to contact with said specified body part of said user.   
     
     
         6 . The method of  claim 1 , wherein said sensors comprise pressure sensor, and wherein said analyzing comprises:
 detecting, by said processor via said pressure sensor, a pressure applied to said mobile hardware device with respect to contact with said specified body part of said user.   
     
     
         7 . The method of  claim 1 , wherein said specified body part of said user comprises a hand of said user, and wherein said portion of said specified body part comprises a thumb of said user. 
     
     
         8 . The method of  claim 1 , wherein said modifying further comprises scaling a size of said specified portion of said user interaction portion based on a detected size and shape of said specified body part of said user. 
     
     
         9 . The method of  claim 8 , wherein said detected size and shape of said specified body part of said user is detected via said sensors. 
     
     
         10 . The method of  claim 1 , further comprising:
 generating, by said processor based on analysis of said modifying, self-learning computer code configured to be executed for predicting additional modifications of additional GUIs of mobile devices of said user.   
     
     
         11 . The method of  claim 1 , further comprising:
 providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in the control hardware, said code being executed by the computer processor to implement: said automatically determining, said enabling, said analyzing, said determining said specified body part, said determining said specified portion, said modifying, said receiving, said presenting, and said retrieving.   
     
     
         12 . A computer program product, comprising a computer readable hardware storage device storing a computer readable program code, said computer readable program code comprising an algorithm that when executed by a processor of a mobile hardware device of a user implements an automated mobile device prediction and detection improvement method, said method comprising:
 automatically determining, by said processor, a user interaction portion of said mobile device, wherein said user interaction portion of said mobile hardware device is associated with executing predictive content selection actions;   enabling, by said processor in response to a command from said user, predictive content keyboard functionality with respect to a graphical user interface (GUI) of said mobile hardware device;   analyzing, by said processor, sensor data retrieved from sensors of said mobile hardware device;   determining, by said processor based on results of said analyzing, a specified body part of said user currently being utilized for supporting and retaining said mobile hardware device;   determining, by said processor based on results of said determining, a specified portion of said user interaction portion for presenting predictive content associated with input data retrieved via a keyboard of said GUI;   modifying, by said processor based on said results of said determining, said GUI such that said specified portion of said user interaction portion is presented at a specified location of said GUI associated with said specified body part of said user;   receiving, by said processor from said user, input text data;   presenting, by said processor within said specified portion of said user interaction portion at specified location of said GUI, predictive terms associated with said input text data such that said predictive terms are accessible via a portion of said specified body part of said user; and   retrieving, by said processor via said portion of said specified body part of said user, a selection of a first predictive term of said predictive terms.   
     
     
         13 . The computer program product of  claim 12 , wherein said automatically determining said user interaction portion of said mobile device comprises:
 retrieving, by said processor from a remote database, a user profile describing user reachable portions of said user interaction portion.   
     
     
         14 . The computer program product of  claim 12 , wherein said automatically determining said user interaction portion of said mobile device comprises:
 detecting, by said processor via said sensors, said portion of said specified body part of said user currently able to access said user interaction portion.   
     
     
         15 . The computer program product of  claim 12 , wherein said user interaction portion of said mobile is reachable via a thumb of said user. 
     
     
         16 . The computer program product of  claim 12 , wherein said sensors comprise an accelerometer and a gyroscope and wherein said analyzing comprises:
 detecting, by said processor via said accelerometer, vibrations initiated via said specified body part of said user; and   detecting, by said processor via said gyroscope, an angle of said specified body part of said user with respect to said mobile hardware device.   
     
     
         17 . The computer program product of  claim 12 , wherein said sensors comprise a temperature sensor, and wherein said analyzing comprises:
 detecting, by said processor via said temperature sensor, a temperature of said mobile hardware device with respect to contact with said specified body part of said user.   
     
     
         18 . The computer program product of  claim 12 , wherein said sensors comprise pressure sensor, and wherein said analyzing comprises:
 detecting, by said processor via said pressure sensor, a pressure applied to said mobile hardware device with respect to contact with said specified body part of said user.   
     
     
         19 . The computer program product of  claim 12 , wherein said specified body part of said user comprises a hand of said user, and wherein said portion of said specified body part comprises a thumb of said user. 
     
     
         20 . A mobile hardware device comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements an automated mobile device prediction and detection improvement method comprising:
 automatically determining, by said processor, a user interaction portion of said mobile device, wherein said user interaction portion of said mobile hardware device is associated with executing predictive content selection actions;   enabling, by said processor in response to a command from said user, predictive content keyboard functionality with respect to a graphical user interface (GUI) of said mobile hardware device;   analyzing, by said processor, sensor data retrieved from sensors of said mobile hardware device;   determining, by said processor based on results of said analyzing, a specified body part of said user currently being utilized for supporting and retaining said mobile hardware device;   determining, by said processor based on results of said determining, a specified portion of said user interaction portion for presenting predictive content associated with input data retrieved via a keyboard of said GUI;   modifying, by said processor based on said results of said determining, said GUI such that said specified portion of said user interaction portion is presented at a specified location of said GUI associated with said specified body part of said user;   receiving, by said processor from said user, input text data;   presenting, by said processor within said specified portion of said user interaction portion at specified location of said GUI, predictive terms associated with said input text data such that said predictive terms are accessible via a portion of said specified body part of said user; and   retrieving, by said processor via said portion of said specified body part of said user, a selection of a first predictive term of said predictive terms.